Biology subjects

Shannon, B.

Publications and source records attributed to Shannon, B..

6 recordsLinked to original sources

bioRxiv2025

Adjuvants to improve efficacy of miticides in managed honey bee (Apis mellifera) colonies to control Varroa destructor

Beekeepers must manage Varroa destructor mites to maintain colony health. Large-scale beekeepers often use chemical treatments (miticides) to manage this pest. Miticide resistance drives a need for compounds with alternative modes of toxic action that can be used in a rotation as part of a Varroa management plan. This research aimed to determine the efficacy of oxalic acid, clove oil, and fenpyroximate when delivered in glycerin soaked in strips and combined with a range of bee-safe adjuvants. Adjuvants are a group of compounds used in plant pesticide applications to increase the spreading and penetration of a pesticide. Laboratory cage trials tested a miticidal active ingredient (oxalic acid, clove oil, or fenpyroximate) and an adjuvant (Ecostep BC-12(R), Ecostep SE-11(R), Ecostep AE-13(R), Ecostep CE-13(R), or Silwet L-7500(R)) in glycerin-soaked strips; field trials evaluated oxalic acid combined with Ecostep BC-12(R) adjuvant in glycerin-soaked strips. Field trials with oxalic acid and adjuvant in glycerin caused a significant decrease in Varroa in year 1 and a significant reduction in Varroa, relative to the solvent control, in year 2. On the other hand, field trials with oxalic acid alone did not reduce Varroa loads in colonies relative to the solvent control. Additionally, mite drop data indicate increased speed for the miticidal effect when an adjuvant is included with oxalic acid. This research informs formulation chemistries for oxalic acid and other miticides to help beekeepers maintain healthy hives.

zoology↗

bioRxiv2023

In-vivo multicellular control of gene expression in microbial consortia

This paper presents an innovative approach in synthetic biology, focusing on the engineering of biomolecular feedback control systems within microbial consortia to achieve robust and precise regulation of desired phenotypes. Traditional biomolecular control strategies, while effective, are predominantly confined to single-cell applications, limiting their complexity and adaptability due to metabolic constraints. We propose a novel methodology that distributes control functionalities across different cell populations within a microbial consortium. This approach leverages the division of labor and cooperative interactions among microbial populations, significantly enhancing flexibility and robustness. We build on the foundation of synthetically engineered microbial consortia, known for their applications in complex compound production and advanced computational processes. However, the challenge of implementing a distributed feedback control loop for precise phenotype regulation in synthetic communities has remained unaddressed. Our work closes this gap by developing and validating an in-vivo feedback control loop distributed across a bacterial consortium, specifically designed using two Escherichia coli strains. These strains are engineered to perform the three essential control functions: computation, sensing, and actuation. We employ orthogonal quorum sensing signaling molecules for communication between the controller and target cell populations. Through in-vivo experiments, we compare closed-loop and open-loop configurations to demonstrate the effectiveness of our approach. The results show that our distributed control system can regulate gene expression levels in target populations with high precision and robustness, even in the presence of consortium composition variations. This feature is particularly vital for practical applications in synthetic biology where stability and adaptability are crucial. Our study not only addresses a significant gap in synthetic biology literature but also opens avenues for more complex and reliable synthetic biology applications.

synthetic biology↗

bioRxiv2020

ChipSeg: an automatic tool to segment bacteria and mammalian cells cultured in microfluidic devices

Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. While such image segmentation applications have been previously reported, there is in the literature a lack of open-source and documented code for the community. We describe ChipSeg, a computational tool to segment bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy. The method is based on thresholding and uses the same core functions for both cell types. It allows to segment individual cells in high cell-density microfluidic devices, to quantify fluorescence protein expression over a time-lapse experiment and to track individual cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customised for other experimental settings and research aims.

synthetic biology↗

bioRxiv2020

Cheetah: a computational toolkit for cybergenetic control

Advances in microscopy, microfluidics and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups that hinder reproducibility. To address this, we introduce Cheetah - a flexible computational toolkit that simplifies the integration of real-time microscopy analysis with algorithms for cellular control. Central to the platform is an image segmentation system based on the versatile U-Net convolutional neural network. This is supplemented with functionality to robustly count, characterise and control cells over time. We demonstrate Cheetahs core capabilities by analysing long-term bacterial and mammalian cell growth and by dynamically controlling protein expression in mammalian cells. In all cases, Cheetahs segmentation accuracy exceeds that of a commonly used thresholding-based method, allowing for more accurate control signals to be generated. Availability of this easy-to-use platform will make control engineering techniques more accessible and offer new ways to probe and manipulate living cells.

synthetic biology↗

bioRxiv2020

In vivo Feedback Control of an Antithetic Molecular-Titration Motif in Escherichia coli using Microfluidics

We study both in silico and in vivo the real-time feedback control of a molecular titration motif that has been earmarked as a fundamental component of antithetic and multicellular feedback control schemes in E. coli. We show that an external feedback control strategy can successfully regulate the average fluorescence output of a bacterial cell population to a desired constant level in real-time. We also provide in silico evidence that the same strategy can be used to track a time-varying reference signal where the set-point is switched to a different value halfway through the experiment. We use the experimental data to refine and parameterize an in silico model of the motif that can be used as an error computation module in future embedded or multicellular control experiments.

synthetic biology↗

bioRxiv2019

A low cost, open source Turbidostat design for in-vivo control experiments in Synthetic Biology

To characterise the dynamics of new engineered systems in Synthetic biology, continuous culture platforms are required. In this paper, after a brief review of the existing machines present in literature, we describe the design and the implementation of a new flexible and low cost turbidostat for in-vivo control experiments. Then, the results of a 3 hours long experiment of control of the Optical Density is reported. Since the foundation of our design is flexibility, in this work we also discuss some possible extensions of our design, with particular attention to their application to validate in-vivo multicellular control design.

synthetic biology↗